Impact of flight disturbances on airborne radar tracking

Stefano Fortunati; Alfonso Farina; Fulvio Gini; Antonio Graziano; Maria S. Greco; Sofia Giompapa

doi:10.1109/TAES.2012.6237620

Impact of flight disturbances on airborne radar tracking

Stefano Fortunati, Alfonso Farina, Fulvio Gini, Antonio Graziano, Maria S. Greco, Sofia Giompapa

Research output: Contribution to journal › Article › peer-review

Abstract

This correspondence is devoted to the study of the impact of flight disturbances due to the atmospheric turbulence on airborne radar tracking. The performance of a turbulence-ignorant tracking filter is assessed in a turbulent simulated scenario. The turbulence is modelled according to the Dryden model, a correlated, zero-mean, Gaussian random process. A quasi-ellipsoidal racetrack course is chosen for the air platform that carries the radar. The performance of the turbulence-ignorant tracking algorithm is analyzed in terms of mean value and standard deviation of the estimation errors for each component of the position and velocity vectors and compared with the posterior Cramer-Rao lower bound (PCRLB), evaluated for the ideal case of absence of platform vibrations.

Original language	English
Article number	6237620
Pages (from-to)	2698-2710
Number of pages	13
Journal	IEEE Transactions on Aerospace and Electronic Systems
Volume	48
Issue number	3
DOIs	https://doi.org/10.1109/TAES.2012.6237620
Publication status	Published - 23 Jul 2012
Externally published	Yes

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10.1109/TAES.2012.6237620

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abstract = "This correspondence is devoted to the study of the impact of flight disturbances due to the atmospheric turbulence on airborne radar tracking. The performance of a turbulence-ignorant tracking filter is assessed in a turbulent simulated scenario. The turbulence is modelled according to the Dryden model, a correlated, zero-mean, Gaussian random process. A quasi-ellipsoidal racetrack course is chosen for the air platform that carries the radar. The performance of the turbulence-ignorant tracking algorithm is analyzed in terms of mean value and standard deviation of the estimation errors for each component of the position and velocity vectors and compared with the posterior Cramer-Rao lower bound (PCRLB), evaluated for the ideal case of absence of platform vibrations.",

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AU - Fortunati, Stefano

AU - Farina, Alfonso

AU - Gini, Fulvio

AU - Graziano, Antonio

AU - Greco, Maria S.

AU - Giompapa, Sofia

PY - 2012/7/23

Y1 - 2012/7/23

N2 - This correspondence is devoted to the study of the impact of flight disturbances due to the atmospheric turbulence on airborne radar tracking. The performance of a turbulence-ignorant tracking filter is assessed in a turbulent simulated scenario. The turbulence is modelled according to the Dryden model, a correlated, zero-mean, Gaussian random process. A quasi-ellipsoidal racetrack course is chosen for the air platform that carries the radar. The performance of the turbulence-ignorant tracking algorithm is analyzed in terms of mean value and standard deviation of the estimation errors for each component of the position and velocity vectors and compared with the posterior Cramer-Rao lower bound (PCRLB), evaluated for the ideal case of absence of platform vibrations.

AB - This correspondence is devoted to the study of the impact of flight disturbances due to the atmospheric turbulence on airborne radar tracking. The performance of a turbulence-ignorant tracking filter is assessed in a turbulent simulated scenario. The turbulence is modelled according to the Dryden model, a correlated, zero-mean, Gaussian random process. A quasi-ellipsoidal racetrack course is chosen for the air platform that carries the radar. The performance of the turbulence-ignorant tracking algorithm is analyzed in terms of mean value and standard deviation of the estimation errors for each component of the position and velocity vectors and compared with the posterior Cramer-Rao lower bound (PCRLB), evaluated for the ideal case of absence of platform vibrations.

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Impact of flight disturbances on airborne radar tracking

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